short coiled-coil proteinGenealiases: HRIHFB2072 · SCOCO · UNC-69
Q-omics provides the consensus-scored SCOC profile across patient tissues and cancer cell-line models. SCOC expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SCOC is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, SCOC RNA expression shows 19,653 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRC, and UVM as cancer lineages where SCOC shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for SCOC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCOC survival associations across molecular data types. SCOC RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCOC RNA expression–survival associations across cancer types. High SCOC expression shows unfavorable associations in HNSC, CESC, LIHC and GBM, but favorable associations in KIRC and UCEC. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for SCOC RNA expression.
This table summarizes SCOC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SCOC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCOC shows lower tumor expression in KIRC, THCA and KIRP and higher tumor expression in LIHC, LUAD and CHOL. The KIRC box plot shows higher SCOC RNA expression in normal versus tumor tissue (log2 FC = −0.947, t-test p < 0.001).
This table shows molecular features associated with SCOC in patient tissues and cancer cell lines. In patient samples, SCOC shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SCOC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
